Graph-to-Sequence
26 papers with code • 2 benchmarks • 3 datasets
Mapping an input graph to a sequence of vectors.
Libraries
Use these libraries to find Graph-to-Sequence models and implementations
WebNLG
EventNarrative
ENT-DESC
Most implemented papers
Modeling Global and Local Node Contexts for Text Generation from Knowledge Graphs
UKPLab/kg2text
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Recent graph-to-text models generate text from graph-based data using either global or local aggregation to learn node representations.
ENT-DESC: Entity Description Generation by Exploring Knowledge Graph
LiyingCheng95/EntityDescriptionGeneration
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EMNLP 2020
Previous works on knowledge-to-text generation take as input a few RDF triples or key-value pairs conveying the knowledge of some entities to generate a natural language description.
GPT-too: A language-model-first approach for AMR-to-text generation
IBM/GPT-too-AMR2text
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ACL 2020
Meaning Representations (AMRs) are broad-coverage sentence-level semantic graphs.
Permutation invariant graph-to-sequence model for template-free retrosynthesis and reaction prediction
Synthesis planning and reaction outcome prediction are two fundamental problems in computer-aided organic chemistry for which a variety of data-driven approaches have emerged.
Predicting Parking Lot Availability by Graph-to-Sequence Model: A Case Study with SmartSantander
Nowadays, so as to improve services and urban areas livability, multiple smart city initiatives are being carried out throughout the world.
UAlign: Pushing the Limit of Template-free Retrosynthesis Prediction with Unsupervised SMILES Alignment
Single-step retrosynthesis prediction, a crucial step in the planning process, has witnessed a surge in interest in recent years due to advancements in AI for science.
